Overview

Dataset statistics

Number of variables17
Number of observations27553
Missing cells114
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory39.3 MiB
Average record size in memory1.5 KiB

Variable types

Text5
Categorical5
Numeric6
Boolean1

Alerts

shipping_weight has unique valuesUnique
customer_reviews_count has 285 (1.0%) zerosZeros
discount_offered has 12325 (44.7%) zerosZeros

Reproduction

Analysis started2024-04-04 15:31:29.919579
Analysis finished2024-04-04 15:31:48.998308
Duration19.08 seconds
Software versionydata-profiling vv4.7.0
Download configurationconfig.json

Variables

Distinct23539
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Memory size2.2 MiB
2024-04-04T21:01:49.210236image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length131
Median length101
Mean length33.826008
Min length3

Characters and Unicode

Total characters932008
Distinct characters92
Distinct categories14 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20565 ?
Unique (%)74.6%

Sample

1st rowGarlic Oil - Vegetarian Capsule 500 mg
2nd rowWater Bottle - Orange
3rd rowBrass Angle Deep - Plain, No.2
4th rowCereal Flip Lid Container/Storage Jar - Assorted Colour
5th rowCreme Soft Soap - For Hands & Body
ValueCountFrequency (%)
19933
 
12.7%
with 1860
 
1.2%
for 1406
 
0.9%
oil 1362
 
0.9%
organic 1156
 
0.7%
tea 899
 
0.6%
steel 878
 
0.6%
cream 843
 
0.5%
powder 839
 
0.5%
green 820
 
0.5%
Other values (11431) 127425
80.9%
2024-04-04T21:01:49.695657image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
129979
 
13.9%
e 76648
 
8.2%
a 69522
 
7.5%
i 53022
 
5.7%
r 51235
 
5.5%
o 46558
 
5.0%
t 42530
 
4.6%
n 40590
 
4.4%
l 39793
 
4.3%
s 30772
 
3.3%
Other values (82) 351359
37.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 615884
66.1%
Uppercase Letter 138202
 
14.8%
Space Separator 130103
 
14.0%
Dash Punctuation 18072
 
1.9%
Decimal Number 14492
 
1.6%
Other Punctuation 12813
 
1.4%
Math Symbol 1317
 
0.1%
Open Punctuation 557
 
0.1%
Close Punctuation 557
 
0.1%
Connector Punctuation 4
 
< 0.1%
Other values (4) 7
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 76648
12.4%
a 69522
11.3%
i 53022
 
8.6%
r 51235
 
8.3%
o 46558
 
7.6%
t 42530
 
6.9%
n 40590
 
6.6%
l 39793
 
6.5%
s 30772
 
5.0%
u 22975
 
3.7%
Other values (19) 142239
23.1%
Uppercase Letter
ValueCountFrequency (%)
S 16494
 
11.9%
C 15277
 
11.1%
P 12031
 
8.7%
B 11849
 
8.6%
M 9023
 
6.5%
F 8119
 
5.9%
D 6415
 
4.6%
A 6088
 
4.4%
T 5836
 
4.2%
G 5770
 
4.2%
Other values (17) 41300
29.9%
Other Punctuation
ValueCountFrequency (%)
, 6046
47.2%
& 3112
24.3%
/ 2385
 
18.6%
% 561
 
4.4%
. 481
 
3.8%
' 156
 
1.2%
: 27
 
0.2%
" 25
 
0.2%
! 18
 
0.1%
* 2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
0 3921
27.1%
1 2851
19.7%
2 1960
13.5%
5 1569
10.8%
3 1146
 
7.9%
4 849
 
5.9%
7 667
 
4.6%
6 554
 
3.8%
9 493
 
3.4%
8 482
 
3.3%
Space Separator
ValueCountFrequency (%)
129979
99.9%
  124
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
- 18055
99.9%
17
 
0.1%
Math Symbol
ValueCountFrequency (%)
+ 1315
99.8%
| 2
 
0.2%
Open Punctuation
ValueCountFrequency (%)
( 551
98.9%
[ 6
 
1.1%
Close Punctuation
ValueCountFrequency (%)
) 551
98.9%
] 6
 
1.1%
Control
ValueCountFrequency (%)
2
66.7%
1
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%
Currency Symbol
ValueCountFrequency (%)
1
100.0%
Initial Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 754086
80.9%
Common 177922
 
19.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 76648
 
10.2%
a 69522
 
9.2%
i 53022
 
7.0%
r 51235
 
6.8%
o 46558
 
6.2%
t 42530
 
5.6%
n 40590
 
5.4%
l 39793
 
5.3%
s 30772
 
4.1%
u 22975
 
3.0%
Other values (46) 280441
37.2%
Common
ValueCountFrequency (%)
129979
73.1%
- 18055
 
10.1%
, 6046
 
3.4%
0 3921
 
2.2%
& 3112
 
1.7%
1 2851
 
1.6%
/ 2385
 
1.3%
2 1960
 
1.1%
5 1569
 
0.9%
+ 1315
 
0.7%
Other values (26) 6729
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 931814
> 99.9%
None 173
 
< 0.1%
Punctuation 20
 
< 0.1%
Currency Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
129979
 
13.9%
e 76648
 
8.2%
a 69522
 
7.5%
i 53022
 
5.7%
r 51235
 
5.5%
o 46558
 
5.0%
t 42530
 
4.6%
n 40590
 
4.4%
l 39793
 
4.3%
s 30772
 
3.3%
Other values (73) 351165
37.7%
None
ValueCountFrequency (%)
  124
71.7%
 34
 
19.7%
è 12
 
6.9%
é 2
 
1.2%
â 1
 
0.6%
Punctuation
ValueCountFrequency (%)
17
85.0%
2
 
10.0%
1
 
5.0%
Currency Symbols
ValueCountFrequency (%)
1
100.0%

category
Categorical

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.8 MiB
Beauty & Hygiene
7867 
Gourmet & World Food
4690 
Kitchen, Garden & Pets
3580 
Snacks & Branded Foods
2814 
Foodgrains, Oil & Masala
2676 
Other values (6)
5926 

Length

Max length24
Median length22
Mean length19.086633
Min length9

Characters and Unicode

Total characters525894
Distinct characters36
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBeauty & Hygiene
2nd rowKitchen, Garden & Pets
3rd rowCleaning & Household
4th rowCleaning & Household
5th rowBeauty & Hygiene

Common Values

ValueCountFrequency (%)
Beauty & Hygiene 7867
28.6%
Gourmet & World Food 4690
17.0%
Kitchen, Garden & Pets 3580
13.0%
Snacks & Branded Foods 2814
 
10.2%
Foodgrains, Oil & Masala 2676
 
9.7%
Cleaning & Household 2674
 
9.7%
Beverages 884
 
3.2%
Bakery, Cakes & Dairy 851
 
3.1%
Baby Care 610
 
2.2%
Fruits & Vegetables 557
 
2.0%

Length

2024-04-04T21:01:49.967086image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
26059
27.4%
beauty 7867
 
8.3%
hygiene 7867
 
8.3%
gourmet 4690
 
4.9%
world 4690
 
4.9%
food 4690
 
4.9%
kitchen 3580
 
3.8%
garden 3580
 
3.8%
pets 3580
 
3.8%
snacks 2814
 
3.0%
Other values (18) 25825
27.1%

Most occurring characters

ValueCountFrequency (%)
67689
 
12.9%
e 54178
 
10.3%
a 36017
 
6.8%
o 35088
 
6.7%
n 28679
 
5.5%
d 26752
 
5.1%
& 26059
 
5.0%
r 22203
 
4.2%
i 21231
 
4.0%
t 21181
 
4.0%
Other values (26) 186817
35.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 355506
67.6%
Uppercase Letter 69183
 
13.2%
Space Separator 67689
 
12.9%
Other Punctuation 33516
 
6.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 54178
15.2%
a 36017
10.1%
o 35088
9.9%
n 28679
8.1%
d 26752
 
7.5%
r 22203
 
6.2%
i 21231
 
6.0%
t 21181
 
6.0%
s 20783
 
5.8%
y 18046
 
5.1%
Other values (9) 71348
20.1%
Uppercase Letter
ValueCountFrequency (%)
B 13026
18.8%
F 11087
16.0%
H 10541
15.2%
G 8270
12.0%
W 4690
 
6.8%
C 4135
 
6.0%
K 3580
 
5.2%
P 3580
 
5.2%
M 3026
 
4.4%
S 2814
 
4.1%
Other values (4) 4434
 
6.4%
Other Punctuation
ValueCountFrequency (%)
& 26059
77.8%
, 7457
 
22.2%
Space Separator
ValueCountFrequency (%)
67689
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 424689
80.8%
Common 101205
 
19.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 54178
 
12.8%
a 36017
 
8.5%
o 35088
 
8.3%
n 28679
 
6.8%
d 26752
 
6.3%
r 22203
 
5.2%
i 21231
 
5.0%
t 21181
 
5.0%
s 20783
 
4.9%
y 18046
 
4.2%
Other values (23) 140531
33.1%
Common
ValueCountFrequency (%)
67689
66.9%
& 26059
 
25.7%
, 7457
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 525894
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
67689
 
12.9%
e 54178
 
10.3%
a 36017
 
6.8%
o 35088
 
6.7%
n 28679
 
5.5%
d 26752
 
5.1%
& 26059
 
5.0%
r 22203
 
4.2%
i 21231
 
4.0%
t 21181
 
4.0%
Other values (26) 186817
35.5%
Distinct90
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size1.7 MiB
2024-04-04T21:01:50.318083image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length16.65296
Min length3

Characters and Unicode

Total characters458839
Distinct characters52
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowHair Care
2nd rowStorage & Accessories
3rd rowPooja Needs
4th rowBins & Bathroom Ware
5th rowBath & Hand Wash
ValueCountFrequency (%)
16895
 
20.8%
care 3641
 
4.5%
skin 2294
 
2.8%
accessories 1738
 
2.1%
snacks 1562
 
1.9%
fruits 1305
 
1.6%
health 1233
 
1.5%
bath 1202
 
1.5%
medicine 1133
 
1.4%
drinks 1080
 
1.3%
Other values (154) 49001
60.4%
2024-04-04T21:01:50.747911image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
53531
 
11.7%
e 46870
 
10.2%
s 37848
 
8.2%
a 34826
 
7.6%
r 28344
 
6.2%
i 25535
 
5.6%
o 20256
 
4.4%
n 18783
 
4.1%
t 16907
 
3.7%
& 16895
 
3.7%
Other values (42) 159044
34.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 318746
69.5%
Uppercase Letter 64189
 
14.0%
Space Separator 53531
 
11.7%
Other Punctuation 22373
 
4.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 46870
14.7%
s 37848
11.9%
a 34826
10.9%
r 28344
8.9%
i 25535
8.0%
o 20256
 
6.4%
n 18783
 
5.9%
t 16907
 
5.3%
c 15809
 
5.0%
l 11375
 
3.6%
Other values (16) 62193
19.5%
Uppercase Letter
ValueCountFrequency (%)
S 11331
17.7%
C 10528
16.4%
B 5983
9.3%
D 5733
8.9%
F 4630
7.2%
H 3772
 
5.9%
M 3375
 
5.3%
N 3140
 
4.9%
A 2503
 
3.9%
P 2371
 
3.7%
Other values (12) 10823
16.9%
Other Punctuation
ValueCountFrequency (%)
& 16895
75.5%
, 4673
 
20.9%
' 805
 
3.6%
Space Separator
ValueCountFrequency (%)
53531
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 382935
83.5%
Common 75904
 
16.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 46870
 
12.2%
s 37848
 
9.9%
a 34826
 
9.1%
r 28344
 
7.4%
i 25535
 
6.7%
o 20256
 
5.3%
n 18783
 
4.9%
t 16907
 
4.4%
c 15809
 
4.1%
l 11375
 
3.0%
Other values (38) 126382
33.0%
Common
ValueCountFrequency (%)
53531
70.5%
& 16895
 
22.3%
, 4673
 
6.2%
' 805
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 458839
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
53531
 
11.7%
e 46870
 
10.2%
s 37848
 
8.2%
a 34826
 
7.6%
r 28344
 
6.2%
i 25535
 
5.6%
o 20256
 
4.4%
n 18783
 
4.1%
t 16907
 
3.7%
& 16895
 
3.7%
Other values (42) 159044
34.7%

brand
Text

Distinct2313
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size1.5 MiB
2024-04-04T21:01:51.057090image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length34
Median length24
Mean length8.4656117
Min length1

Characters and Unicode

Total characters233253
Distinct characters70
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique505 ?
Unique (%)1.8%

Sample

1st rowSri Sri Ayurveda
2nd rowMastercook
3rd rowTrm
4th rowNakoda
5th rowNivea
ValueCountFrequency (%)
bb 1217
 
3.1%
fresho 821
 
2.1%
royal 558
 
1.4%
home 480
 
1.2%
organic 376
 
1.0%
the 351
 
0.9%
ayurveda 265
 
0.7%
dp 250
 
0.6%
239
 
0.6%
himalaya 211
 
0.5%
Other values (2544) 34341
87.8%
2024-04-04T21:01:51.551140image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 24336
 
10.4%
e 19406
 
8.3%
r 13962
 
6.0%
o 13712
 
5.9%
13216
 
5.7%
i 12779
 
5.5%
n 9977
 
4.3%
t 9688
 
4.2%
l 9486
 
4.1%
s 9122
 
3.9%
Other values (60) 97569
41.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 169626
72.7%
Uppercase Letter 48459
 
20.8%
Space Separator 13216
 
5.7%
Other Punctuation 1014
 
0.4%
Decimal Number 599
 
0.3%
Dash Punctuation 306
 
0.1%
Math Symbol 32
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 24336
14.3%
e 19406
11.4%
r 13962
 
8.2%
o 13712
 
8.1%
i 12779
 
7.5%
n 9977
 
5.9%
t 9688
 
5.7%
l 9486
 
5.6%
s 9122
 
5.4%
u 5470
 
3.2%
Other values (16) 41688
24.6%
Uppercase Letter
ValueCountFrequency (%)
S 4260
 
8.8%
B 3421
 
7.1%
A 3233
 
6.7%
C 3103
 
6.4%
T 2937
 
6.1%
P 2829
 
5.8%
M 2810
 
5.8%
H 2684
 
5.5%
N 2597
 
5.4%
R 2380
 
4.9%
Other values (16) 18205
37.6%
Decimal Number
ValueCountFrequency (%)
1 123
20.5%
4 121
20.2%
2 105
17.5%
0 75
12.5%
3 48
 
8.0%
8 32
 
5.3%
7 30
 
5.0%
9 27
 
4.5%
5 26
 
4.3%
6 12
 
2.0%
Other Punctuation
ValueCountFrequency (%)
' 400
39.4%
. 333
32.8%
& 254
25.0%
! 27
 
2.7%
Space Separator
ValueCountFrequency (%)
13216
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 306
100.0%
Math Symbol
ValueCountFrequency (%)
+ 32
100.0%
Other Symbol
ValueCountFrequency (%)
° 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 218085
93.5%
Common 15168
 
6.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 24336
 
11.2%
e 19406
 
8.9%
r 13962
 
6.4%
o 13712
 
6.3%
i 12779
 
5.9%
n 9977
 
4.6%
t 9688
 
4.4%
l 9486
 
4.3%
s 9122
 
4.2%
u 5470
 
2.5%
Other values (42) 90147
41.3%
Common
ValueCountFrequency (%)
13216
87.1%
' 400
 
2.6%
. 333
 
2.2%
- 306
 
2.0%
& 254
 
1.7%
1 123
 
0.8%
4 121
 
0.8%
2 105
 
0.7%
0 75
 
0.5%
3 48
 
0.3%
Other values (8) 187
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 233252
> 99.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 24336
 
10.4%
e 19406
 
8.3%
r 13962
 
6.0%
o 13712
 
5.9%
13216
 
5.7%
i 12779
 
5.5%
n 9977
 
4.3%
t 9688
 
4.2%
l 9486
 
4.1%
s 9122
 
3.9%
Other values (59) 97568
41.8%
None
ValueCountFrequency (%)
° 1
100.0%

selling_price
Real number (ℝ)

Distinct3256
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean322.52914
Minimum2.45
Maximum12500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size215.4 KiB
2024-04-04T21:01:51.758124image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum2.45
5-th percentile33
Q195
median190
Q3359
95-th percentile999
Maximum12500
Range12497.55
Interquartile range (IQR)264

Descriptive statistics

Standard deviation486.27743
Coefficient of variation (CV)1.5077007
Kurtosis64.385588
Mean322.52914
Median Absolute Deviation (MAD)112.25
Skewness6.1765497
Sum8886645.5
Variance236465.74
MonotonicityNot monotonic
2024-04-04T21:01:51.946400image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99 406
 
1.5%
199 317
 
1.2%
50 316
 
1.1%
299 302
 
1.1%
150 291
 
1.1%
60 289
 
1.0%
149 260
 
0.9%
225 248
 
0.9%
120 245
 
0.9%
75 241
 
0.9%
Other values (3246) 24638
89.4%
ValueCountFrequency (%)
2.45 1
 
< 0.1%
3 1
 
< 0.1%
5 25
0.1%
6 7
 
< 0.1%
7.5 2
 
< 0.1%
8 1
 
< 0.1%
8.5 2
 
< 0.1%
9 11
< 0.1%
9.5 4
 
< 0.1%
9.9 2
 
< 0.1%
ValueCountFrequency (%)
12500 1
< 0.1%
10090 1
< 0.1%
8184.44 1
< 0.1%
7999 1
< 0.1%
7299 1
< 0.1%
7270 1
< 0.1%
6999 1
< 0.1%
6700 1
< 0.1%
6660 1
< 0.1%
6500 1
< 0.1%

original_price
Real number (ℝ)

Distinct1348
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean382.07387
Minimum3
Maximum12500
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size215.4 KiB
2024-04-04T21:01:52.065487image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile36
Q1100
median220
Q3425
95-th percentile1214
Maximum12500
Range12497
Interquartile range (IQR)325

Descriptive statistics

Standard deviation581.74776
Coefficient of variation (CV)1.5226055
Kurtosis55.736281
Mean382.07387
Median Absolute Deviation (MAD)135
Skewness5.7886985
Sum10527281
Variance338430.46
MonotonicityNot monotonic
2024-04-04T21:01:52.210477image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
199 584
 
2.1%
150 469
 
1.7%
99 465
 
1.7%
50 445
 
1.6%
250 429
 
1.6%
299 423
 
1.5%
60 411
 
1.5%
120 373
 
1.4%
75 347
 
1.3%
300 334
 
1.2%
Other values (1338) 23273
84.5%
ValueCountFrequency (%)
3 1
 
< 0.1%
5 23
 
0.1%
6 1
 
< 0.1%
6.25 2
 
< 0.1%
7.5 6
 
< 0.1%
9 1
 
< 0.1%
9.38 2
 
< 0.1%
10 126
0.5%
11.25 2
 
< 0.1%
12 12
 
< 0.1%
ValueCountFrequency (%)
12500 1
< 0.1%
12245 1
< 0.1%
10769 1
< 0.1%
10695 1
< 0.1%
10090 1
< 0.1%
9695 1
< 0.1%
8969 1
< 0.1%
7875 1
< 0.1%
7645 1
< 0.1%
7400 1
< 0.1%
Distinct426
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 MiB
2024-04-04T21:01:52.571301image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length33
Median length22
Mean length16.843429
Min length4

Characters and Unicode

Total characters464087
Distinct characters60
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)< 0.1%

Sample

1st rowHair Oil & Serum
2nd rowWater & Fridge Bottles
3rd rowLamp & Lamp Oil
4th rowLaundry, Storage Baskets
5th rowBathing Bars & Soaps
ValueCountFrequency (%)
11719
 
14.9%
care 2374
 
3.0%
face 1852
 
2.4%
tea 1096
 
1.4%
other 927
 
1.2%
organic 896
 
1.1%
snacks 830
 
1.1%
body 809
 
1.0%
deodorants 654
 
0.8%
bars 653
 
0.8%
Other values (617) 56772
72.2%
2024-04-04T21:01:53.321210image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
51029
 
11.0%
e 47823
 
10.3%
a 39921
 
8.6%
s 32608
 
7.0%
r 28066
 
6.0%
o 23620
 
5.1%
t 20505
 
4.4%
i 20445
 
4.4%
n 18228
 
3.9%
l 15319
 
3.3%
Other values (50) 166523
35.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 327444
70.6%
Uppercase Letter 67436
 
14.5%
Space Separator 51029
 
11.0%
Other Punctuation 17455
 
3.8%
Dash Punctuation 457
 
0.1%
Open Punctuation 73
 
< 0.1%
Close Punctuation 73
 
< 0.1%
Decimal Number 73
 
< 0.1%
Math Symbol 47
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 47823
14.6%
a 39921
12.2%
s 32608
10.0%
r 28066
8.6%
o 23620
 
7.2%
t 20505
 
6.3%
i 20445
 
6.2%
n 18228
 
5.6%
l 15319
 
4.7%
c 10881
 
3.3%
Other values (16) 70028
21.4%
Uppercase Letter
ValueCountFrequency (%)
C 9832
14.6%
S 9230
13.7%
B 6778
10.1%
F 4909
 
7.3%
P 4568
 
6.8%
M 4563
 
6.8%
T 3568
 
5.3%
D 3407
 
5.1%
O 2917
 
4.3%
G 2597
 
3.9%
Other values (14) 15067
22.3%
Other Punctuation
ValueCountFrequency (%)
& 11719
67.1%
, 5082
29.1%
' 654
 
3.7%
Decimal Number
ValueCountFrequency (%)
5 60
82.2%
2 13
 
17.8%
Space Separator
ValueCountFrequency (%)
51029
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 457
100.0%
Open Punctuation
ValueCountFrequency (%)
( 73
100.0%
Close Punctuation
ValueCountFrequency (%)
) 73
100.0%
Math Symbol
ValueCountFrequency (%)
+ 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 394880
85.1%
Common 69207
 
14.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 47823
 
12.1%
a 39921
 
10.1%
s 32608
 
8.3%
r 28066
 
7.1%
o 23620
 
6.0%
t 20505
 
5.2%
i 20445
 
5.2%
n 18228
 
4.6%
l 15319
 
3.9%
c 10881
 
2.8%
Other values (40) 137464
34.8%
Common
ValueCountFrequency (%)
51029
73.7%
& 11719
 
16.9%
, 5082
 
7.3%
' 654
 
0.9%
- 457
 
0.7%
( 73
 
0.1%
) 73
 
0.1%
5 60
 
0.1%
+ 47
 
0.1%
2 13
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 464087
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
51029
 
11.0%
e 47823
 
10.3%
a 39921
 
8.6%
s 32608
 
7.0%
r 28066
 
6.0%
o 23620
 
5.1%
t 20505
 
4.4%
i 20445
 
4.4%
n 18228
 
3.9%
l 15319
 
3.3%
Other values (50) 166523
35.9%

product_rating
Real number (ℝ)

Distinct70
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9638152
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size215.4 KiB
2024-04-04T21:01:53.621006image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.7
Q13.8
median4.1
Q34.3
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)0.5

Descriptive statistics

Standard deviation0.67115816
Coefficient of variation (CV)0.16932125
Kurtosis5.5623455
Mean3.9638152
Median Absolute Deviation (MAD)0.2
Skewness-1.8846902
Sum109215
Variance0.45045328
MonotonicityNot monotonic
2024-04-04T21:01:53.791303image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 4115
14.9%
4.1 3713
13.5%
4.2 3454
12.5%
4.3 2519
 
9.1%
5 1771
 
6.4%
3.8 1136
 
4.1%
4.4 1128
 
4.1%
3.9 1065
 
3.9%
4.5 978
 
3.5%
3 854
 
3.1%
Other values (60) 6820
24.8%
ValueCountFrequency (%)
1 418
1.5%
1.2 2
 
< 0.1%
1.3 9
 
< 0.1%
1.4 6
 
< 0.1%
1.5 32
 
0.1%
1.6 3
 
< 0.1%
1.65 8
 
< 0.1%
1.7 22
 
0.1%
1.75 22
 
0.1%
1.8 22
 
0.1%
ValueCountFrequency (%)
5 1771
6.4%
4.95 22
 
0.1%
4.9 65
 
0.2%
4.8 202
 
0.7%
4.75 5
 
< 0.1%
4.7 344
 
1.2%
4.7 2
 
< 0.1%
4.65 12
 
< 0.1%
4.6 336
 
1.2%
4.55 6
 
< 0.1%
Distinct21943
Distinct (%)80.0%
Missing114
Missing (%)0.4%
Memory size22.0 MiB
2024-04-04T21:01:54.042354image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length4486
Median length1853
Mean length486.74933
Min length7

Characters and Unicode

Total characters13355915
Distinct characters151
Distinct categories19 ?
Distinct scripts2 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18955 ?
Unique (%)69.1%

Sample

1st rowThis Product contains Garlic Oil that is known to help proper digestion, maintain proper cholesterol levels, support cardiovascular and also build immunity. For Beauty tips, tricks & more visit https://bigbasket.blog/
2nd rowEach product is microwave safe (without lid), refrigerator safe, dishwasher safe and can also be used for re-heating food and not for cooking. All containers come with airtight lids and a wide variety of attractive colours. Stack these stylish and colourful containers in your kitchen with ease and for a look-good factor.
3rd rowA perfect gift for all occasions, be it your mother, sister, in-laws, boss or your friends, this beautiful designer piece wherever placed, is sure to beautify the surroundings Traditional design This type diya has been used for Diwali and All other Festivals for centuries. Sturdy and easy to carry The feet keep it balanced to ensure safety. Wonderful Oil Lamp made in Brass also called as Jyoti. This is a handcrafted piece of Indian brass Deepak.
4th rowMultipurpose container with an attractive design and made from food-grade plastic for your hygiene and safety ideal for storing pulses. Grains, spices, and more with easy opening and closing flip-open lid. Strong, durable and transparent body for longevity and easy identification of contents. Multipurpose storage solution for your daily needs stores your everyday food essentials in style with the Nakoda container set. With transparent bodies, you can easily identify your stored items without having to open the lids. These containers are ideal for storing a large variety of items such as food grains, snacks and pulses to sugar, spices, condiments and more. Featuring unique flip-open lids, you can easily open and close this container without any hassles. The Nakoda container is made from high-quality food-grade and BPA-free plastic that is 100% safe for storing food items. You can safely store your food items in this container without worrying about contamination and harmful toxins. As they are constructed using highly durable virgin plastic, this container will last for a long time even with regular use. This container can enhance the overall look of your kitchen decor. Being dishwasher safe, cleaning and maintaining this container is an easy task. You can also use a simple soap solution to manually wash and retain their looks for a long time.
5th rowNivea Creme Soft Soap gives your skin the best care that it must get. The soft bar consists of Vitamins F and Almonds which are really skin gracious and help you get great skin. It provides the skin with moisture and leaves behind flawless and smooth skin. It makes sure that your body is totally free of germs & dirt and at the same time well nourished.For Beauty tips, tricks & more visit https://bigbasket.blog/
ValueCountFrequency (%)
and 97426
 
4.5%
the 79096
 
3.6%
of 52740
 
2.4%
a 49551
 
2.3%
is 47101
 
2.2%
to 44341
 
2.0%
with 34155
 
1.6%
it 33400
 
1.5%
in 30836
 
1.4%
for 30626
 
1.4%
Other values (38596) 1687171
77.2%
2024-04-04T21:01:54.532400image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2145981
16.1%
e 1198118
 
9.0%
a 923195
 
6.9%
t 845672
 
6.3%
i 829169
 
6.2%
o 759377
 
5.7%
s 738277
 
5.5%
n 724287
 
5.4%
r 695448
 
5.2%
l 473574
 
3.5%
Other values (141) 4022817
30.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10408950
77.9%
Space Separator 2153748
 
16.1%
Uppercase Letter 375295
 
2.8%
Other Punctuation 287414
 
2.2%
Decimal Number 56035
 
0.4%
Dash Punctuation 39893
 
0.3%
Control 16057
 
0.1%
Open Punctuation 4993
 
< 0.1%
Final Punctuation 4971
 
< 0.1%
Close Punctuation 4070
 
< 0.1%
Other values (9) 4489
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1198118
11.5%
a 923195
 
8.9%
t 845672
 
8.1%
i 829169
 
8.0%
o 759377
 
7.3%
s 738277
 
7.1%
n 724287
 
7.0%
r 695448
 
6.7%
l 473574
 
4.5%
h 432946
 
4.2%
Other values (29) 2788887
26.8%
Uppercase Letter
ValueCountFrequency (%)
T 43178
 
11.5%
I 36643
 
9.8%
S 29158
 
7.8%
C 27794
 
7.4%
A 26776
 
7.1%
P 20907
 
5.6%
B 20613
 
5.5%
M 18556
 
4.9%
F 16063
 
4.3%
E 13396
 
3.6%
Other values (22) 122211
32.6%
Other Punctuation
ValueCountFrequency (%)
. 132008
45.9%
, 107106
37.3%
& 9681
 
3.4%
/ 9187
 
3.2%
: 7351
 
2.6%
' 6091
 
2.1%
% 6089
 
2.1%
! 4541
 
1.6%
1492
 
0.5%
? 1176
 
0.4%
Other values (10) 2692
 
0.9%
Decimal Number
ValueCountFrequency (%)
0 17513
31.3%
1 11508
20.5%
2 5969
 
10.7%
3 4693
 
8.4%
5 4408
 
7.9%
9 3318
 
5.9%
4 3082
 
5.5%
6 2161
 
3.9%
8 1929
 
3.4%
7 1454
 
2.6%
Math Symbol
ValueCountFrequency (%)
+ 584
38.7%
¬ 488
32.4%
| 310
20.6%
> 81
 
5.4%
= 24
 
1.6%
~ 14
 
0.9%
< 6
 
0.4%
× 1
 
0.1%
Control
ValueCountFrequency (%)
10783
67.2%
5264
32.8%
 5
 
< 0.1%
4
 
< 0.1%
1
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 3773
75.6%
1083
 
21.7%
88
 
1.8%
[ 46
 
0.9%
{ 3
 
0.1%
Other Symbol
ValueCountFrequency (%)
265
55.4%
® 88
 
18.4%
° 67
 
14.0%
¦ 42
 
8.8%
© 16
 
3.3%
Modifier Symbol
ValueCountFrequency (%)
´ 77
54.2%
^ 47
33.1%
˜ 9
 
6.3%
` 6
 
4.2%
¨ 3
 
2.1%
Other Number
ValueCountFrequency (%)
¾ 34
54.0%
½ 12
 
19.0%
¼ 11
 
17.5%
³ 4
 
6.3%
¹ 2
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 39233
98.3%
625
 
1.6%
35
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 4024
98.9%
] 43
 
1.1%
} 3
 
0.1%
Space Separator
ValueCountFrequency (%)
2145981
99.6%
  7767
 
0.4%
Final Punctuation
ValueCountFrequency (%)
4770
96.0%
201
 
4.0%
Currency Symbol
ValueCountFrequency (%)
¢ 942
53.8%
809
46.2%
Initial Punctuation
ValueCountFrequency (%)
262
53.7%
226
46.3%
Other Letter
ValueCountFrequency (%)
º 31
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 19
100.0%
Format
ValueCountFrequency (%)
­ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10784255
80.7%
Common 2571660
 
19.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2145981
83.4%
. 132008
 
5.1%
, 107106
 
4.2%
- 39233
 
1.5%
0 17513
 
0.7%
1 11508
 
0.4%
10783
 
0.4%
& 9681
 
0.4%
/ 9187
 
0.4%
  7767
 
0.3%
Other values (70) 80893
 
3.1%
Latin
ValueCountFrequency (%)
e 1198118
 
11.1%
a 923195
 
8.6%
t 845672
 
7.8%
i 829169
 
7.7%
o 759377
 
7.0%
s 738277
 
6.8%
n 724287
 
6.7%
r 695448
 
6.4%
l 473574
 
4.4%
h 432946
 
4.0%
Other values (61) 3164192
29.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13330738
99.8%
None 15121
 
0.1%
Punctuation 8973
 
0.1%
Currency Symbols 809
 
< 0.1%
Letterlike Symbols 265
 
< 0.1%
Modifier Letters 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2145981
16.1%
e 1198118
 
9.0%
a 923195
 
6.9%
t 845672
 
6.3%
i 829169
 
6.2%
o 759377
 
5.7%
s 738277
 
5.5%
n 724287
 
5.4%
r 695448
 
5.2%
l 473574
 
3.6%
Other values (88) 3997640
30.0%
None
ValueCountFrequency (%)
  7767
51.4%
à 1742
 
11.5%
¢ 942
 
6.2%
 895
 
5.9%
ƒ 761
 
5.0%
â 551
 
3.6%
¬ 488
 
3.2%
š 412
 
2.7%
é 293
 
1.9%
Æ 274
 
1.8%
Other values (29) 996
 
6.6%
Punctuation
ValueCountFrequency (%)
4770
53.2%
1492
 
16.6%
1083
 
12.1%
625
 
7.0%
262
 
2.9%
226
 
2.5%
201
 
2.2%
99
 
1.1%
92
 
1.0%
88
 
1.0%
Currency Symbols
ValueCountFrequency (%)
809
100.0%
Letterlike Symbols
ValueCountFrequency (%)
265
100.0%
Modifier Letters
ValueCountFrequency (%)
˜ 9
100.0%

customer_reviews_count
Real number (ℝ)

ZEROS 

Distinct101
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.962363
Minimum0
Maximum100
Zeros285
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size215.4 KiB
2024-04-04T21:01:54.675960image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q125
median50
Q375
95-th percentile95
Maximum100
Range100
Interquartile range (IQR)50

Descriptive statistics

Standard deviation29.016464
Coefficient of variation (CV)0.58076645
Kurtosis-1.1893464
Mean49.962363
Median Absolute Deviation (MAD)25
Skewness-0.00090906917
Sum1376613
Variance841.95521
MonotonicityNot monotonic
2024-04-04T21:01:54.796421image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
57 313
 
1.1%
30 309
 
1.1%
55 303
 
1.1%
85 300
 
1.1%
84 300
 
1.1%
29 299
 
1.1%
41 297
 
1.1%
54 297
 
1.1%
5 295
 
1.1%
27 295
 
1.1%
Other values (91) 24545
89.1%
ValueCountFrequency (%)
0 285
1.0%
1 279
1.0%
2 252
0.9%
3 249
0.9%
4 274
1.0%
5 295
1.1%
6 257
0.9%
7 277
1.0%
8 286
1.0%
9 273
1.0%
ValueCountFrequency (%)
100 249
0.9%
99 282
1.0%
98 265
1.0%
97 281
1.0%
96 272
1.0%
95 259
0.9%
94 265
1.0%
93 272
1.0%
92 253
0.9%
91 252
0.9%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Spring
6920 
Autumn
6913 
Winter
6888 
Summer
6832 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters165318
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSpring
2nd rowWinter
3rd rowWinter
4th rowSpring
5th rowWinter

Common Values

ValueCountFrequency (%)
Spring 6920
25.1%
Autumn 6913
25.1%
Winter 6888
25.0%
Summer 6832
24.8%

Length

2024-04-04T21:01:54.902238image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-04T21:01:54.995466image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
spring 6920
25.1%
autumn 6913
25.1%
winter 6888
25.0%
summer 6832
24.8%

Most occurring characters

ValueCountFrequency (%)
n 20721
12.5%
u 20658
12.5%
r 20640
12.5%
m 20577
12.4%
i 13808
8.4%
t 13801
8.3%
S 13752
8.3%
e 13720
8.3%
p 6920
 
4.2%
g 6920
 
4.2%
Other values (2) 13801
8.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 137765
83.3%
Uppercase Letter 27553
 
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 20721
15.0%
u 20658
15.0%
r 20640
15.0%
m 20577
14.9%
i 13808
10.0%
t 13801
10.0%
e 13720
10.0%
p 6920
 
5.0%
g 6920
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
S 13752
49.9%
A 6913
25.1%
W 6888
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 165318
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 20721
12.5%
u 20658
12.5%
r 20640
12.5%
m 20577
12.4%
i 13808
8.4%
t 13801
8.3%
S 13752
8.3%
e 13720
8.3%
p 6920
 
4.2%
g 6920
 
4.2%
Other values (2) 13801
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 165318
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 20721
12.5%
u 20658
12.5%
r 20640
12.5%
m 20577
12.4%
i 13808
8.4%
t 13801
8.3%
S 13752
8.3%
e 13720
8.3%
p 6920
 
4.2%
g 6920
 
4.2%
Other values (2) 13801
8.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
False
13798 
True
13755 
ValueCountFrequency (%)
False 13798
50.1%
True 13755
49.9%
2024-04-04T21:01:55.088457image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

shipping_weight
Real number (ℝ)

UNIQUE 

Distinct27553
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.7421256
Minimum0.50001909
Maximum4.9994545
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size215.4 KiB
2024-04-04T21:01:55.302374image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0.50001909
5-th percentile0.7199187
Q11.6223284
median2.7316283
Q33.8711147
95-th percentile4.7667891
Maximum4.9994545
Range4.4994354
Interquartile range (IQR)2.2487863

Descriptive statistics

Standard deviation1.2988901
Coefficient of variation (CV)0.47367999
Kurtosis-1.2035706
Mean2.7421256
Median Absolute Deviation (MAD)1.120613
Skewness0.0087873916
Sum75553.788
Variance1.6871154
MonotonicityNot monotonic
2024-04-04T21:01:55.493342image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.658145101 1
 
< 0.1%
2.996287868 1
 
< 0.1%
1.234084558 1
 
< 0.1%
1.323410347 1
 
< 0.1%
3.642127181 1
 
< 0.1%
2.032509629 1
 
< 0.1%
3.712205811 1
 
< 0.1%
2.214819836 1
 
< 0.1%
3.528093883 1
 
< 0.1%
1.500542031 1
 
< 0.1%
Other values (27543) 27543
> 99.9%
ValueCountFrequency (%)
0.500019085 1
< 0.1%
0.5002530176 1
< 0.1%
0.5002837105 1
< 0.1%
0.5004462318 1
< 0.1%
0.5005447629 1
< 0.1%
0.5007505231 1
< 0.1%
0.5008530157 1
< 0.1%
0.5008746339 1
< 0.1%
0.5008984649 1
< 0.1%
0.5009099545 1
< 0.1%
ValueCountFrequency (%)
4.999454522 1
< 0.1%
4.999270003 1
< 0.1%
4.998453078 1
< 0.1%
4.997891362 1
< 0.1%
4.997832623 1
< 0.1%
4.997697309 1
< 0.1%
4.997644018 1
< 0.1%
4.997508084 1
< 0.1%
4.996451461 1
< 0.1%
4.996431625 1
< 0.1%

bundle_indicator
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.5 MiB
Bundle
13854 
Individual
13699 

Length

Max length10
Median length6
Mean length7.988749
Min length6

Characters and Unicode

Total characters220114
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowIndividual
2nd rowBundle
3rd rowBundle
4th rowIndividual
5th rowIndividual

Common Values

ValueCountFrequency (%)
Bundle 13854
50.3%
Individual 13699
49.7%

Length

2024-04-04T21:01:55.611372image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-04T21:01:55.787099image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
bundle 13854
50.3%
individual 13699
49.7%

Most occurring characters

ValueCountFrequency (%)
d 41252
18.7%
u 27553
12.5%
n 27553
12.5%
l 27553
12.5%
i 27398
12.4%
B 13854
 
6.3%
e 13854
 
6.3%
I 13699
 
6.2%
v 13699
 
6.2%
a 13699
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 192561
87.5%
Uppercase Letter 27553
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 41252
21.4%
u 27553
14.3%
n 27553
14.3%
l 27553
14.3%
i 27398
14.2%
e 13854
 
7.2%
v 13699
 
7.1%
a 13699
 
7.1%
Uppercase Letter
ValueCountFrequency (%)
B 13854
50.3%
I 13699
49.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 220114
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
d 41252
18.7%
u 27553
12.5%
n 27553
12.5%
l 27553
12.5%
i 27398
12.4%
B 13854
 
6.3%
e 13854
 
6.3%
I 13699
 
6.2%
v 13699
 
6.2%
a 13699
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 220114
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
d 41252
18.7%
u 27553
12.5%
n 27553
12.5%
l 27553
12.5%
i 27398
12.4%
B 13854
 
6.3%
e 13854
 
6.3%
I 13699
 
6.2%
v 13699
 
6.2%
a 13699
 
6.2%
Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
Other
9257 
Male
9167 
Female
9129 

Length

Max length6
Median length5
Mean length4.9986208
Min length4

Characters and Unicode

Total characters137727
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFemale
2nd rowFemale
3rd rowFemale
4th rowOther
5th rowMale

Common Values

ValueCountFrequency (%)
Other 9257
33.6%
Male 9167
33.3%
Female 9129
33.1%

Length

2024-04-04T21:01:55.959119image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-04T21:01:56.063468image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
other 9257
33.6%
male 9167
33.3%
female 9129
33.1%

Most occurring characters

ValueCountFrequency (%)
e 36682
26.6%
a 18296
13.3%
l 18296
13.3%
O 9257
 
6.7%
t 9257
 
6.7%
h 9257
 
6.7%
r 9257
 
6.7%
M 9167
 
6.7%
F 9129
 
6.6%
m 9129
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 110174
80.0%
Uppercase Letter 27553
 
20.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 36682
33.3%
a 18296
16.6%
l 18296
16.6%
t 9257
 
8.4%
h 9257
 
8.4%
r 9257
 
8.4%
m 9129
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
O 9257
33.6%
M 9167
33.3%
F 9129
33.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 137727
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 36682
26.6%
a 18296
13.3%
l 18296
13.3%
O 9257
 
6.7%
t 9257
 
6.7%
h 9257
 
6.7%
r 9257
 
6.7%
M 9167
 
6.7%
F 9129
 
6.6%
m 9129
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 137727
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 36682
26.6%
a 18296
13.3%
l 18296
13.3%
O 9257
 
6.7%
t 9257
 
6.7%
h 9257
 
6.7%
r 9257
 
6.7%
M 9167
 
6.7%
F 9129
 
6.6%
m 9129
 
6.6%

discount_offered
Real number (ℝ)

ZEROS 

Distinct2663
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.825113
Minimum0
Maximum83.67
Zeros12325
Zeros (%)44.7%
Negative0
Negative (%)0.0%
Memory size215.4 KiB
2024-04-04T21:01:56.204442image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5
Q320
95-th percentile41.71
Maximum83.67
Range83.67
Interquartile range (IQR)20

Descriptive statistics

Standard deviation14.624822
Coefficient of variation (CV)1.2367595
Kurtosis0.88533476
Mean11.825113
Median Absolute Deviation (MAD)5
Skewness1.2180555
Sum325817.35
Variance213.88541
MonotonicityNot monotonic
2024-04-04T21:01:56.317101image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 12325
44.7%
10 1712
 
6.2%
20 1467
 
5.3%
15 1065
 
3.9%
5 864
 
3.1%
25 801
 
2.9%
30 604
 
2.2%
50 309
 
1.1%
40 236
 
0.9%
2 170
 
0.6%
Other values (2653) 8000
29.0%
ValueCountFrequency (%)
0 12325
44.7%
0.2 1
 
< 0.1%
0.28 1
 
< 0.1%
0.34 1
 
< 0.1%
0.42 1
 
< 0.1%
0.49 1
 
< 0.1%
0.54 1
 
< 0.1%
0.67 1
 
< 0.1%
0.75 1
 
< 0.1%
0.77 1
 
< 0.1%
ValueCountFrequency (%)
83.67 1
< 0.1%
82.51 1
< 0.1%
81.2 1
< 0.1%
80.98 1
< 0.1%
80.5 1
< 0.1%
80 1
< 0.1%
79.24 2
< 0.1%
78.7 1
< 0.1%
77.99 2
< 0.1%
77.48 2
< 0.1%

brand_scale
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.4 MiB
medium
17825 
low
6339 
high
3389 

Length

Max length6
Median length6
Mean length5.0638043
Min length3

Characters and Unicode

Total characters139523
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowmedium
2nd rowmedium
3rd rowmedium
4th rowmedium
5th rowmedium

Common Values

ValueCountFrequency (%)
medium 17825
64.7%
low 6339
 
23.0%
high 3389
 
12.3%

Length

2024-04-04T21:01:56.471913image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-04T21:01:56.560905image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
medium 17825
64.7%
low 6339
 
23.0%
high 3389
 
12.3%

Most occurring characters

ValueCountFrequency (%)
m 35650
25.6%
i 21214
15.2%
e 17825
12.8%
d 17825
12.8%
u 17825
12.8%
h 6778
 
4.9%
l 6339
 
4.5%
o 6339
 
4.5%
w 6339
 
4.5%
g 3389
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 139523
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m 35650
25.6%
i 21214
15.2%
e 17825
12.8%
d 17825
12.8%
u 17825
12.8%
h 6778
 
4.9%
l 6339
 
4.5%
o 6339
 
4.5%
w 6339
 
4.5%
g 3389
 
2.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 139523
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
m 35650
25.6%
i 21214
15.2%
e 17825
12.8%
d 17825
12.8%
u 17825
12.8%
h 6778
 
4.9%
l 6339
 
4.5%
o 6339
 
4.5%
w 6339
 
4.5%
g 3389
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 139523
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
m 35650
25.6%
i 21214
15.2%
e 17825
12.8%
d 17825
12.8%
u 17825
12.8%
h 6778
 
4.9%
l 6339
 
4.5%
o 6339
 
4.5%
w 6339
 
4.5%
g 3389
 
2.4%

Interactions

2024-04-04T21:01:47.696823image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:39.849600image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:41.462557image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:43.093587image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:45.038381image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:46.715637image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:47.823883image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:40.114602image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:41.683985image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:43.423630image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:45.279261image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:46.942912image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:47.944668image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:40.437013image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:41.978755image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:43.687638image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:45.639907image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:47.079852image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:48.050665image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:40.658016image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:42.324580image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:43.982628image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:45.907900image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:47.234215image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:48.160153image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:40.965016image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:42.585682image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:44.364127image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:46.131916image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:47.409026image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:48.259994image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:41.223009image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:42.866690image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:44.719070image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:46.357728image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-04-04T21:01:47.548951image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Missing values

2024-04-04T21:01:48.461779image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-04T21:01:48.775877image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

product_titlecategoryproduct_subcategorybrandselling_priceoriginal_priceproduct_typeproduct_ratingproduct_descriptioncustomer_reviews_countseasonal_indicatorpromotion_indicatorshipping_weightbundle_indicatorcustomer_demographicsdiscount_offeredbrand_scale
0Garlic Oil - Vegetarian Capsule 500 mgBeauty & HygieneHair CareSri Sri Ayurveda220.0220.0Hair Oil & Serum4.1This Product contains Garlic Oil that is known to help proper digestion, maintain proper cholesterol levels, support cardiovascular and also build immunity. For Beauty tips, tricks & more visit https://bigbasket.blog/7SpringYes0.658145IndividualFemale0.00medium
1Water Bottle - OrangeKitchen, Garden & PetsStorage & AccessoriesMastercook180.0180.0Water & Fridge Bottles2.3Each product is microwave safe (without lid), refrigerator safe, dishwasher safe and can also be used for re-heating food and not for cooking. All containers come with airtight lids and a wide variety of attractive colours. Stack these stylish and colourful containers in your kitchen with ease and for a look-good factor.54WinterNo4.734585BundleFemale0.00medium
2Brass Angle Deep - Plain, No.2Cleaning & HouseholdPooja NeedsTrm119.0250.0Lamp & Lamp Oil3.4A perfect gift for all occasions, be it your mother, sister, in-laws, boss or your friends, this beautiful designer piece wherever placed, is sure to beautify the surroundings Traditional design This type diya has been used for Diwali and All other Festivals for centuries. Sturdy and easy to carry The feet keep it balanced to ensure safety. Wonderful Oil Lamp made in Brass also called as Jyoti. This is a handcrafted piece of Indian brass Deepak.31WinterNo2.024140BundleFemale52.40medium
3Cereal Flip Lid Container/Storage Jar - Assorted ColourCleaning & HouseholdBins & Bathroom WareNakoda149.0176.0Laundry, Storage Baskets3.7Multipurpose container with an attractive design and made from food-grade plastic for your hygiene and safety ideal for storing pulses. Grains, spices, and more with easy opening and closing flip-open lid. Strong, durable and transparent body for longevity and easy identification of contents. Multipurpose storage solution for your daily needs stores your everyday food essentials in style with the Nakoda container set. With transparent bodies, you can easily identify your stored items without having to open the lids. These containers are ideal for storing a large variety of items such as food grains, snacks and pulses to sugar, spices, condiments and more. Featuring unique flip-open lids, you can easily open and close this container without any hassles.\nThe Nakoda container is made from high-quality food-grade and BPA-free plastic that is 100% safe for storing food items. You can safely store your food items in this container without worrying about contamination and harmful toxins. As they are constructed using highly durable virgin plastic, this container will last for a long time even with regular use. This container can enhance the overall look of your kitchen decor. Being dishwasher safe, cleaning and maintaining this container is an easy task. You can also use a simple soap solution to manually wash and retain their looks for a long time.49SpringNo3.869239IndividualOther15.34medium
4Creme Soft Soap - For Hands & BodyBeauty & HygieneBath & Hand WashNivea162.0162.0Bathing Bars & Soaps4.4Nivea Creme Soft Soap gives your skin the best care that it must get. The soft bar consists of Vitamins F and Almonds which are really skin gracious and help you get great skin. It provides the skin with moisture and leaves behind flawless and smooth skin. It makes sure that your body is totally free of germs & dirt and at the same time well nourished.For Beauty tips, tricks & more visit https://bigbasket.blog/74WinterYes0.812489IndividualMale0.00medium
5Germ - Removal Multipurpose WipesCleaning & HouseholdAll Purpose CleanersNature Protect169.0199.0Disinfectant Spray & Cleaners3.3Stay protected from contamination with Multipurpose Germ Removal Wipes by Nature Protect, a quality product by Hindustan Unilever Limited, the makers of Surf Excel and Lifebuoy. Infused with neem extract Nature Protect Multipurpose Germ removal wipes helps in cleaning and 99.9% germ removal^. Neem extracts are known to have the power of 100 bio-actives with both anti-viral and anti-bacterial capabilities.\nWipes made from 100% biodegradable fabric and balanced with skin’s pH level, our on-the-go hygiene wipes are safe to use on not just surfaces, but human skin, so you can disinfect any exposed parts of your body – such as your hands, elbows, or wrists – as well as the surfaces they’ve touched.  A thorough cleaning with on-the-go hygiene wipes helps in keeping surfaces hygienically clean, both inside and outside your home. Packaged neatly to enable quick, easy removal, these on-the-go hygiene wipes will help you stay protected whether you stay indoors or move out and about.\n^ As per lab test conducted on representative organisms.* Always spot test on hidden area to check compatibility.76SpringYes1.202923IndividualOther15.08low
6Multani MatiBeauty & HygieneSkin CareSatinance58.058.0Face Care3.6Satinance multani matti is an excellent skin toner and astringent. reduces oiliness and while nourishing the skin, keeps it soft and grime. improves complexion by facilitating better blood circulation. For Beauty tips, tricks & more visit https://bigbasket.blog/99WinterYes0.907624IndividualFemale0.00medium
7Hand Sanitizer - 70% Alcohol BaseBeauty & HygieneBath & Hand WashBionova250.0250.0Hand Wash & Sanitizers4.070%Alcohol based is gentle of hand leaves skin soft and moist with a good fragrance. It is really safe for the skin.86WinterYes3.895517BundleMale0.00medium
8Biotin & Collagen Volumizing Hair Shampoo + Biotin & Collagen Hair ConditionerBeauty & HygieneHair CareStBotanica1098.01098.0Shampoo & Conditioner3.5An exclusive blend with Vitamin B7 Biotin, Hydrolyzed collagen, Oat Extract along with premium & organic cold-pressed ingredients helps to infuse nutrients into every strand and creates the appearance of thicker, fuller healthier looking hair. This powerful formula helps volumize even the skinniest strands into fuller and more abundant looking locks. It is safe for color-treated hair and safe for all hair types. St Botanica Biotin & Collagen Hair Conditioner has been specially formulated to repair dry & damaged hair for full, thick, voluminous, shiny & healthy looking hair! The amazing hair conditioner ingredients include Biotin, Hydrolyzed Collagen, Pro-Vitamin B5, Vitamin E, & Hydrolyzed Silk Proteins for glistening looking hair. Biotin and Collagen, infused with most efficacious natural extracts not only promotes healthy hair growth but also prevents hair dryness, increases the elasticity of the hair cortex, thereby strengthening hair, minimizing hair breakage and helping hair grow longer, healthier and thicker. PLUMP IT UP: the nutrient-rich, plump-it-up power of this haircare infused with ProVitamin B7 biotin and collagen helps give each strand of hair a beautiful boost, this dynamic duo will leave your hair feeling thicker, fuller, and looking oh, so healthy.9SummerYes1.769944IndividualOther0.00medium
9Scrub Pad - Anti- Bacterial, RegularCleaning & HouseholdMops, Brushes & ScrubsScotch brite20.020.0Utensil Scrub-Pad, Glove4.3Scotch Brite Anti- Bacterial Scrub Pad thoroughly cleanses dishes and keeps the kitchen utensils squeaky clean with a pleasant neem fragrance. The scrub is gentle on the hands and does not wear off easily, while eliminating bacteria and making your utensils sparkle and look as good as new with every wash.65WinterYes2.421016IndividualOther0.00medium
product_titlecategoryproduct_subcategorybrandselling_priceoriginal_priceproduct_typeproduct_ratingproduct_descriptioncustomer_reviews_countseasonal_indicatorpromotion_indicatorshipping_weightbundle_indicatorcustomer_demographicsdiscount_offeredbrand_scale
27543Toilet Cleaning Brush - Round With Holder (Big)Cleaning & HouseholdMops, Brushes & ScrubsLiao189.00349.0Toilet & Other Brushes3.8This round toilet brush is made up of virgin quality plastic handle and acid-proof polypropylene bristles. It is easy to grip, can be washed repeatedly, and it cleanses the toilet efficiently and completely. Product can be only returned if it is not used and is in packed condition.74WinterNo1.962549IndividualFemale45.85medium
27544Organic Powder - Garam MasalaFoodgrains, Oil & MasalaOrganic StaplesOrganic Tattva152.00160.0Organic Masalas & Spices4.2Organic Tattva Garam masala is a famous spice blend used all over India and neighboring countries too. It is prepared of more than 10 types of spices, and is included in small quantities at the end of the cuisine process, or along with the tempering. It can be used only or along with other seasonings and spice powders. It has a spicy flavor but is not fiery hot similar to chili powder.91WinterYes1.575774IndividualMale5.00medium
27545Powder - BakingSnacks & Branded FoodsReady To Cook & EatKwality38.0038.0Home Baking3.7Kwality Baking Powder Directions for use: Use 10g of Kwality baking powder for baking 450g of flour mix. Mix throughly with the flour in dry state by sifting flour & baking powder together two or three times essentially. In order to have the best velvety texture, volume and lightness, the ready dough should immediately be put in the oven.19WinterYes2.646258BundleOther0.00low
27546Apple Cider Vinegar ShampooBeauty & HygieneHair CareMorpheme Remedies499.00499.0Shampoo & Conditioner5.0Say no to dull, lifeless, dry and damaged hair with Morpheme Remedies Apple Cider Vinegar Shampoo made with nutritive organic apple cider vinegar & rich in proven effective ingredients. The perfect deep cleansing head wash helps to get rid your hair residue, build-up caused by styling products. Our formulation also contains Vitamin E, B5 to moisturize, nurture and condition the hair. Added Shea Butter locks in moisture to keep the scalp nourished and hydrated. Tea Tree Oil famous for its anti-fungal and antiseptic benefits, help heals and fights itch, dryness, and irritation. The precious oils of Golden Virgin Jojoba, Sweet Almond, and Castor help soothe, rejuvenate & hydrates hair and scalp while encouraging hair growth. Cruelty-free product tested only on humans with the intent and goal of restoring hair and giving our users the fullest. Result: Natural, soft hair alongside a beautiful sheen unmatched with other formulas. Free from parabens, sulfates and silicones. Safe & suitable for all hair types. Clarify & Restore: Created to gently but thoroughly remove product buildup and repair damaged follicles without stripping hair of moisture. Soothe scalp and renew hair for healthy beautiful hair50WinterNo2.432741IndividualOther0.00medium
27547Papad - Garlic DiscoSnacks & Branded FoodsReady To Cook & EatAtish61.0061.0Papads, Ready To Fry4.0Papads are prepared from urad dal flour and spiced with taste. They are supplied roasted on an open flame, which creates them fluffy and crunchy appetizers.80AutumnYes2.030996BundleFemale0.00medium
27548Wottagirl! Perfume Spray - Heaven, ClassicBeauty & HygieneFragrances & DeosLayerr199.20249.0Perfume3.9Layerr brings you Wottagirl Classic fragrant body splashes. For the confident, smart, genuine woman who doesnt get caught up in fads, diets and all things nonsense; comes a range of pure, exquisite fragrances that are just as pure, beautiful, resilient and bold.75AutumnYes1.992988BundleOther20.00medium
27549RosemaryGourmet & World FoodCooking & Baking NeedsPuramate67.5075.0Herbs, Seasonings & Rubs4.0Puramate rosemary is enough to transform a dish into something\r\nextraordinary. It is vibrant , dynamic ,aromatic and a perfect flavor booster.\r\nSprinkle some in your , breads & baked goods , salads, sautéed vegetables,\r\ncurries, fried rice and even dips and sauces, as well as herbal teas and\r\nseasoning blends and they can lend that instant zing. Pairs well with bay, garlic,\r\nmarjoram, oregano, parsley, sage, savory, and thyme.65AutumnNo2.893314BundleFemale10.00medium
27550Peri-Peri Sweet Potato ChipsGourmet & World FoodSnacks, Dry Fruits, NutsFabBox200.00200.0Nachos & Chips3.8We have taken the richness of Sweet Potatoes (Shakarkand) and given it a spicy delicious Peri Peri twist! The crispiness is unlike anything before and before you know it, you would have finished the whole pack even before the movie introductions would have been over! :p\r\r\n\r\r\nThe best part is that these chips are non-fried, which means they have almost 82% less oil than standard market chips. So yes, you can be on a diet and still relish chips like never before!61AutumnYes3.644294IndividualFemale0.00medium
27551Green Tea - Pure OriginalBeveragesTeaTetley396.00495.0Tea Bags4.2Tetley Green Tea with its refreshing pure, original flavour contains five times more antioxidants than fruits and vegetables. A cup of Tetley Natural Green Tea helps cleanse from within and eliminates all those pollutants and toxins that our bodies are exposed to on a daily basis!! Rejuvenate yourself every day with a cup of Tetley Natural Green Tea.7SummerNo4.540101IndividualOther20.00medium
27552United Dreams Go Far DeodorantBeauty & HygieneMen's GroomingUnited Colors Of Benetton214.53390.0Men's Deodorants4.5The new mens fragrance from the United Dreams collection is dedicated to any man who loves setting his sights high. This cologne with frizzy hints of brackenwood, perfectly embodies a person who refuses to limit himself to whats possible. Hints of bitter orange, grapefruit and lemon combine with aromatic mint, nutmeg, sage and geranium. A mix that is intensified by exotic dashes of patchouli, vetiver, musk and amber.65SpringYes1.718303BundleOther44.99medium